Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles
Abstract The Eastern Pacific leatherback turtle population (Dermochelys coriacea) has declined precipitously in recent years. One of the major causes is bycatch from coastal and pelagic fisheries. Fisheries observations are often underutilized, despite strong potential for this data to affect policy...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
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| Series: | Conservation Science and Practice |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/csp2.349 |
| _version_ | 1827792926098325504 |
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| author | Jennie Hannah Degenford Dong Liang Helen Bailey Aimee L. Hoover Patricia Zarate Jorge Azócar Daniel Devia Joanna Alfaro‐Shigueto Jeffery C. Mangel Nelly de Paz Javier Quinones Davila David Sarmiento Barturen Juan M. Rguez‐Baron Amanda S. Williard Christina Fahy Nicole Barbour George L. Shillinger |
| author_facet | Jennie Hannah Degenford Dong Liang Helen Bailey Aimee L. Hoover Patricia Zarate Jorge Azócar Daniel Devia Joanna Alfaro‐Shigueto Jeffery C. Mangel Nelly de Paz Javier Quinones Davila David Sarmiento Barturen Juan M. Rguez‐Baron Amanda S. Williard Christina Fahy Nicole Barbour George L. Shillinger |
| author_sort | Jennie Hannah Degenford |
| collection | DOAJ |
| description | Abstract The Eastern Pacific leatherback turtle population (Dermochelys coriacea) has declined precipitously in recent years. One of the major causes is bycatch from coastal and pelagic fisheries. Fisheries observations are often underutilized, despite strong potential for this data to affect policy. In this study, we created a spatiotemporal species distribution model that synthesizes fisheries observations with remotely sensed environmental data. The model will be developed into a dynamic management tool for the Eastern Pacific leatherback population. We obtained leatherback observation data from multiple fisheries that have operated in the Southeast Pacific (2001–2018). A dynamic Poisson point process model was applied to predict leatherback intensity (observation per unit area) as a function of dynamic environmental covariates. This model serves as a tool for application by managers and stakeholders toward the reduction of leatherback turtle bycatch and provides a modeling framework for analyzing fisheries observations from other vulnerable populations and species. |
| first_indexed | 2024-03-11T18:10:08Z |
| format | Article |
| id | doaj.art-62a1aef1d419443ab3d6cd75d415280d |
| institution | Directory Open Access Journal |
| issn | 2578-4854 |
| language | English |
| last_indexed | 2024-03-11T18:10:08Z |
| publishDate | 2021-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Conservation Science and Practice |
| spelling | doaj.art-62a1aef1d419443ab3d6cd75d415280d2023-10-16T14:51:41ZengWileyConservation Science and Practice2578-48542021-02-0132n/an/a10.1111/csp2.349Using fisheries observation data to develop a predictive species distribution model for endangered sea turtlesJennie Hannah Degenford0Dong Liang1Helen Bailey2Aimee L. Hoover3Patricia Zarate4Jorge Azócar5Daniel Devia6Joanna Alfaro‐Shigueto7Jeffery C. Mangel8Nelly de Paz9Javier Quinones Davila10David Sarmiento Barturen11Juan M. Rguez‐Baron12Amanda S. Williard13Christina Fahy14Nicole Barbour15George L. Shillinger16Chesapeake Biological Laboratory University of Maryland Center for Environmental Science Solomons Maryland USAChesapeake Biological Laboratory University of Maryland Center for Environmental Science Solomons Maryland USAChesapeake Biological Laboratory University of Maryland Center for Environmental Science Solomons Maryland USAChesapeake Biological Laboratory University of Maryland Center for Environmental Science Solomons Maryland USAInstituto de Fomento Pesquero Valparaíso Región de Valparaíso ChileInstituto de Fomento Pesquero Valparaíso Región de Valparaíso ChileInstituto de Fomento Pesquero Valparaíso Región de Valparaíso ChileProDelphinus Lima PeruProDelphinus Lima PeruAreas Costeras y Recursos Marinos Pisco PeruLaboratorio Costero de Pisco, Instituto del Mar del Perú Paracas PeruLaboratorio Costero de Pisco, Instituto del Mar del Perú Paracas PeruJUSTSEA Foundation Bogota ColombiaDepartment of Biology and Marine Biology University of North Carolina Wilmington Wilmington North Carolina USAProtected Resources Division, West Coast Regional Office National Marine Fisheries Service Long Beach California USAChesapeake Biological Laboratory University of Maryland Center for Environmental Science Solomons Maryland USAUpwell, Heritage Harbor Complex Monterey California USAAbstract The Eastern Pacific leatherback turtle population (Dermochelys coriacea) has declined precipitously in recent years. One of the major causes is bycatch from coastal and pelagic fisheries. Fisheries observations are often underutilized, despite strong potential for this data to affect policy. In this study, we created a spatiotemporal species distribution model that synthesizes fisheries observations with remotely sensed environmental data. The model will be developed into a dynamic management tool for the Eastern Pacific leatherback population. We obtained leatherback observation data from multiple fisheries that have operated in the Southeast Pacific (2001–2018). A dynamic Poisson point process model was applied to predict leatherback intensity (observation per unit area) as a function of dynamic environmental covariates. This model serves as a tool for application by managers and stakeholders toward the reduction of leatherback turtle bycatch and provides a modeling framework for analyzing fisheries observations from other vulnerable populations and species.https://doi.org/10.1111/csp2.349dynamic Poisson process modelhabitat‐based modelleatherback turtleSoutheast Pacific Ocean |
| spellingShingle | Jennie Hannah Degenford Dong Liang Helen Bailey Aimee L. Hoover Patricia Zarate Jorge Azócar Daniel Devia Joanna Alfaro‐Shigueto Jeffery C. Mangel Nelly de Paz Javier Quinones Davila David Sarmiento Barturen Juan M. Rguez‐Baron Amanda S. Williard Christina Fahy Nicole Barbour George L. Shillinger Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles Conservation Science and Practice dynamic Poisson process model habitat‐based model leatherback turtle Southeast Pacific Ocean |
| title | Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles |
| title_full | Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles |
| title_fullStr | Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles |
| title_full_unstemmed | Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles |
| title_short | Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles |
| title_sort | using fisheries observation data to develop a predictive species distribution model for endangered sea turtles |
| topic | dynamic Poisson process model habitat‐based model leatherback turtle Southeast Pacific Ocean |
| url | https://doi.org/10.1111/csp2.349 |
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